AGS Data Systems
The Impact of AI and Automation
on Curriculum Development
Derrick Edwards
President and Chief Technology Officer
AGS Data Systems / G*STARS
NCWE Annual Conference
September 26, 2018
AGS Data Systems
Take Away from Today
Working definitions: robotics, automation, AI, Block Chain, etc.
Framework for describing subjectivity to Automation
Discussion of types of career pathways at risk, not at risk, and changing
The larger context of technological change and the Fourth Industrial Revolution
Outline for evaluating curricula relative to these topics
AGS Data Systems
Resources at GSTARS.com/ncwe2018
AGS Data Systems
A Lot of Noise
“13 Jobs That Robots, AI, And Automation Won’t Steal” – Forbes
“3 Reasons You Won’t Mind When AI Replaces Half of All Jobs” – Inc.
“AI Will Put 10 Million Jobs at High Risk” – CBInsights
“10 Jobs That AI Will Replace” – Hubspot
“Robots taking jobs in five year is BS, GE CEO says” – CNBC
“Robots Have been Taking American Jobs, Study Says” – US News
“Automation Taking Jobs” – C-Span
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Definitions
Automation
Any machine that performs a job with reduced levels of human interaction
Most impactful on physically repetitive or predictable work
Robotics ( = automation )Subset of Automation, where manipulation and mobility are involved
Most impactful on complex repetition and social interaction
Artificial Intelligence (AI) and Machine Learning (ML)
Allows computer to learn a task even if humans can’t explain the task
Impacts information processing and remote social interaction
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Careers Being Impacted
“Highly Cited…”
The Future of Employment: How Susceptible Are Jobs To Computerization?
Carl Benedikt Frey and Michael A. Osborne
Oxford University, 2013
http://www.oxfordmartin.ox.ac.uk/downloads/academic/The_Future_of_Employment.pdf
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The Future of Employment: How Susceptible Are Jobs To Computerization?
Rank Probability Occupation
702 0.99 Telemarketers
701 0.99 Title Examiners, Abstractors, and Searchers
700 0.99 Sewers, Hand
699 0.99 Mathematical Technicians
698 0.99 Insurance Underwriters
697 0.99 Watch Repairers
696 0.99 Cargo and Freight Agents
695 0.99 Tax Preparers
694 0.99 Photographic Process Workers and Processing Machine Operators
693 0.99 New Accounts Clerks
692 0.99 Library Technicians
691 0.99 Data Entry Keyers
690 0.98 Timing Device Assemblers and Adjusters
689 0.98 Insurance Claims and Policy Processing Clerks
688 0.98 Brokerage Clerks
687 0.98 Order Clerks
686 0.98 Loan Officers
685 0.98 Insurance Appraisers, Auto Damage
684 0.98 Umpires, Referees, and Other Sports Officials
683 0.98 Tellers
682 0.98 Etchers and Engravers
681 0.98 Packaging and Filling Machine Operators and Tenders
680 0.98 Procurement Clerks
679 0.98 Shipping, Receiving, and Traffic Clerks
678 0.98Milling and Planing Machine Setters, Operators, and Tenders, Metal and Plastic
Rank Probability Occupation
1 0.0028 Recreational Therapists
2 0.003 First-Line Supervisors of Mechanics, Installers, and Repairers
3 0.003 Emergency Management Directors
4 0.0031 Mental Health and Substance Abuse Social Workers
5 0.0033 Audiologists
6 0.0035 Occupational Therapists
7 0.0035 Orthotists and Prosthetists
8 0.0035 Healthcare Social Workers
9 0.0036 Oral and Maxillofacial Surgeons
10 0.0036 First-Line Supervisors of Fire Fighting and Prevention Workers
11 0.0039 Dietitians and Nutritionists
12 0.0039 Lodging Managers
13 0.004 Choreographers
14 0.0041 Sales Engineers
15 0.0042 Physicians and Surgeons
16 0.0042 Instructional Coordinators
17 0.0043 Psychologists, All Other
18 0.0044 First-Line Supervisors of Police and Detectives
19 0.0044 Dentists, General
20 0.0044 Elementary School Teachers, Except Special Education
21 0.0045 Medical Scientists, Except Epidemiologists
22 0.0046 Education Administrators, Elementary and Secondary School
23 0.0046 Podiatrists
24 0.0047 Clinical, Counseling, and School Psychologists
25 0.0048 Mental Health Counselors
Top 25 Bottom 25
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Careers Being Impacted
Predictable and Repetitive Actions• Garment Manufacturing• Brick Laying
Information Collection and Analysis• Tax Preparation
• Insurance Underwriting• Financial Planning
Limited Scope Human Interaction• Customer Service• Home Health Care
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Careers Being Impacted
Let’s talk through a few examples…
Agriculture
Transportation
Middle Management
Construction
Health Care
AGS Data Systems
Careers Being Impacted
Derrick, don’t forget
to show the videos
https://www.youtube.com/watch?v=ir54GLUDXac
https://www.youtube.com/watch?v=GUdF8I9xFX0
https://www.youtube.com/watch?v=rVlhMGQgDkY
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Wages Rates Are a Weak Predictor
Source: O*NET 2014 and McKinsey & Company Analysis
https://www.mckinsey.com/business-functions/digital-mckinsey/our-insights/four-fundamentals-of-workplace-automation
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Geography Is No Predictor
Source: Joshua Wright, EMSI, 2014“Low-Skill Jobs Are Booming, But They’re
at Greatest Risk for Automation”
http://www.economicmodeling.com/2014/10/31/low-skill-jobs-are-booming-but-theyre-at-
greater-risk-for-automation/
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It’s Ultimately About the Cost
“Technology can provide better efficiency and quality with menial tasks, as Webster noted. But employers are
less likely to invest in that technology if there aren’t a high volume of workers to replace, or if it’s more
expensive than really cheap labor.”
JOSHUA WRIGHT, EMSI, OCTOBER 31, 2014“Low-Skill Jobs Are Booming, But They’re at
Greatest Risk for Automation”
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How Do We Predict
Source: McKinsey & Company
https://www.mckinsey.com/business-functions/digital-mckinsey/our-insights/where-machines-could-replace-humans-and-where-they-cant-yet
AGS Data Systems
View at the Industry Level
Source: McKinsey & Company
https://www.mckinsey.com/business-functions/digital-mckinsey/our-insights/where-machines-could-replace-humans-and-where-they-cant-yet
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Five Types of Impact
Job Growth – working with automation (e.g. CNC Operators)
Job Loss – due to automation (e.g. Automotive Welders)
Economic Growth without job growth – warehouse robotics
Income Divergence – warehouse humans
Demand Cascade – top down pressure on existing jobs
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Questions and discussion?
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Traditional Forecasting Tools Issue
Key indicators with historical correlations
Census and surveys of employers
Industry-specific growth estimate research
“A rise in [ fill_in_the_blank ] growth equals an increase in job growth”
Models have a hard time seeing disruptive forces
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Curriculum Analysis Considerations
Construct a simplified protocol for rating subjectivity to automation
Rate each Career Path offered, not just the associated industry
Adjust based on specific forecast of the technological change/impact
Understand how key economic forecasting models account for automation
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Analyze at the Occupation Level
Each individual course should be reviewed and revised to account for
the impact and opportunity of automation.
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Curriculum Development Considerations
Develop curriculum for creating, managing, or supporting automation jobs
Acquire (buy/partner/collaborate) content for extremely short cycle-time
Develop at least one hybrid model with industry partner extending the internship/apprenticeship model
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“On net…”
…some career pathways will disappear, some will be created, but
within the 2-year system our primary goals will be learning to forecast
the impact of technology on specific careers, drastically shorten
curriculum cycle-times, and evolve the structure of our relationship
with employers.
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Complicating Factors
Industrial / Corporate Education
Portable / Micro Credentials
Differentiation
Career Changers
Curricula Cycle-time
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Questions and discussion before
we move on to the future?
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Fourth Industrial Revolution
First: Steam and mechanization, 1800*
Second: Electrification and mass preproduction, 1900*
Third: Computerization and electronics, 1975*
Fourth: Automation and machine intelligence, 2000*
* all dates are “ish”
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Fourth Industrial Revolution
Will come all at once, everywhere
Will, interestingly, have a positive, relative, impact on production costs for advanced economies
May drive adoption of the Universal Basic Income
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Most “Disruptive” Technologies
Block Chain / Smart ContractsEvery Industry, greatest digital transformation since the internet itself
Automation / Robotics (driven by AI)Every job with a physical component
AI / Machine LearningEvery job with an analytical component
Quantum Computing Most highly derivative, will drive entirely new industries and material sciences
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Question and Discussion?
Working definitions: robotics, automation, and AI
Types of career pathways at risk
Impact: loss, growth, income divergence
Issues with traditional forecasting tools
Considering your own curriculum
Resources
AGS Data Systems
Thank You!
Derrick Edwards, President & CTO
AGS Data Systems / G*STARS
gstars.com/ncwe2018
Call, write, or connect with me on LinkedIn
